Software AG acquires JackBe for mashup tooling, real-time analytics

Software AG is adding mashup and real-time analytic capabilities to its lineup with the acquisition of JackBe. Terms of the deal, which was announced Thursday, were not disclosed.

By
Chris Kanaracus
| Aug 22, 2013

| IDG News Service

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Software AG is adding mashup and real-time analytic capabilities to its lineup with the acquisition of JackBe. Terms of the deal, which was announced Thursday, were not disclosed.

JackBe is best known for its Presto mashup software, which allows users to bring together and visualize data from multiple sources. It has also offered a real-time analytics product that incorporates Software AG's Terracotta BigMemory in-memory data grid technology.

The latter product as well as Presto will continue to be offered in stand-alone form.

Software AG is also planning to release a new suite called webMethods Intelligent Business Operations Platform, scheduled for early-access availability in the fourth quarter, it said in a statement.

The suite will include four main components, including an integration layer based on a webMethods product for pulling in data from "systems, processes and sensors," a Software AG representative said via email.

JackBe technology along with a number of webMethods products, including Performance Process Manager, will provide an analytics and mashup layer for filtering and organizing the data.

Finally, Presto will serve as the visualization layer, and Software AG also plans to include templates for common industry processes, such as order-to-cash, to get customers up and running quickly.

The JackBe deal is the latest in a string of smaller acquisitions by Software AG in recent years as it broadens its focus beyond core middleware and process integration.

Adding JackBe to the mix gives Software AG a way to serve business users who want analytics, according to Forrester Research analyst Boris Evelson.

"Most organizations still have enterprise data warehouses and departmental data marts," he said via email. "These require batch processes to integrate the data, aggregate it and denormalize it (flatten it out to optimize for reporting and analytics). This takes time."

While "you won't get complete comprehensive analytics (like time series) by analyzing data directly from operational / transactional data sources, in certain use cases low latency trumps comprehensiveness," he added. "That's JackBe's sweet spot: reporting and analyzing data directly from data sources, bypassing DWs, and doing this in a 'mashup' fashion where business users can get most of the work done on their own, with minimal support from IT."